First thing, load the libraries that will be used.
The first code being used looks at data for college faculty salaries and total compensation from 1995, by Ranks, Tier, and State from 1995. The ranks are Assistant, Associate, and Full. The tier invovled the funding devoted to research vs the amount of funding for teaching; tier I spend mor on research than teaching and award PhD degrees.
Load and clean file:
df <- read.csv("./FacultySalaries_1995.csv")
names(df) <- make_clean_names(names(df))
names(df)## [1] "fed_id" "univ_name" "state"
## [4] "tier" "avg_full_prof_salary" "avg_assoc_prof_salary"
## [7] "avg_assist_prof_salary" "avg_prof_salary_all" "avg_full_prof_comp"
## [10] "avg_assoc_prof_comp" "avg_assist_prof_comp" "avg_prof_comp_all"
## [13] "num_full_profs" "num_assoc_profs" "num_assist_profs"
## [16] "num_instructors" "num_faculty_all"df <- df %>%
pivot_longer(c(avg_full_prof_salary,avg_assoc_prof_salary, avg_assist_prof_salary),
names_prefix = "_salary",
values_to = "salary",
names_to = "rank")
df <- df[!df$tier %in% "VIIB", ]Creation of figure 1:
The ANOVA model tests the influence of “State”, “Tier”, and “Rank” on “Salary.”
aov.df <- aov(salary ~ tier + rank + state, data = df)
summary(aov.df)## Df Sum Sq Mean Sq F value Pr(>F)
## tier 2 8119005 4059503 1116.49 <2e-16 ***
## rank 2 16521237 8260619 2271.92 <2e-16 ***
## state 50 4625868 92517 25.45 <2e-16 ***
## Residuals 3297 11987752 3636
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 128 observations deleted due to missingnessa <- summary(aov.df)
capture.output(a, file= "Salary_ANOVA_Summary.txt") This data is from a collaboration between Young Living Inc. and UVU Microbiology. A number of dead cedar trees were collected and the chemical composition of their essential oil content was measured. The hypothesis was that certain chemicals would degrade over time since they died in fires.
Clean data with chemical compounds:
df2 <- read.csv("./Juniper_Oils.csv")
names(df2)## [1] "SampleID" "Project" "Amplicon"
## [4] "Tree_Species" "BurnYear" "Latitude"
## [7] "Longitude" "Field_Office" "BLM_Fire_Name"
## [10] "Tracking_Number" "alpha.pinene" "para.cymene"
## [13] "alpha.terpineol" "cedr.9.ene" "alpha.cedrene"
## [16] "beta.cedrene" "cis.thujopsene" "alpha.himachalene"
## [19] "beta.chamigrene" "cuparene" "compound.1"
## [22] "alpha.chamigrene" "widdrol" "cedrol"
## [25] "beta.acorenol" "alpha.acorenol" "gamma.eudesmol"
## [28] "beta.eudesmol" "alpha.eudesmol" "cedr.8.en.13.ol"
## [31] "cedr.8.en.15.ol" "compound.2" "thujopsenal"
## [34] "Yield_percent" "Bolt_Surface_Area_cm2" "Raw_Exit_Holes_per_cm2"
## [37] "Raw_Exit_Holes" "Living_Larvae" "ChemTotal"
## [40] "ChemMean" "YearsSinceBurn"df2 <- df2 %>%
pivot_longer(c("alpha.pinene","para.cymene","alpha.terpineol","cedr.9.ene","alpha.cedrene",
"beta.cedrene","cis.thujopsene","alpha.himachalene","beta.chamigrene",
"cuparene","compound.1","alpha.chamigrene","widdrol","cedrol","beta.acorenol",
"alpha.acorenol","gamma.eudesmol","beta.eudesmol","alpha.eudesmol",
"cedr.8.en.13.ol","cedr.8.en.15.ol","compound.2","thujopsenal"),
values_to = "Concentration",
names_to = "ChemicalID")Chemicals of significance (significant, as in P < 0.05) affected by “Years Since Burn.”
mod1 <- glm(data = df2, Concentration ~ YearsSinceBurn * ChemicalID)
summary(mod1)##
## Call:
## glm(formula = Concentration ~ YearsSinceBurn * ChemicalID, data = df2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -15.5340 -0.7152 -0.1333 0.4415 24.6240
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 0.546972 1.365538 0.401
## YearsSinceBurn -0.022323 0.099780 -0.224
## ChemicalIDalpha.cedrene 7.881098 1.931163 4.081
## ChemicalIDalpha.chamigrene -0.097195 1.931163 -0.050
## ChemicalIDalpha.eudesmol 0.361341 1.931163 0.187
## ChemicalIDalpha.himachalene -0.240541 1.931163 -0.125
## ChemicalIDalpha.pinene 0.049025 1.931163 0.025
## ChemicalIDalpha.terpineol 0.445621 1.931163 0.231
## ChemicalIDbeta.acorenol 0.829371 1.931163 0.429
## ChemicalIDbeta.cedrene 2.118457 1.931163 1.097
## ChemicalIDbeta.chamigrene 0.366045 1.931163 0.190
## ChemicalIDbeta.eudesmol 1.428395 1.931163 0.740
## ChemicalIDcedr.8.en.13.ol 7.619740 1.931163 3.946
## ChemicalIDcedr.8.en.15.ol 1.710281 1.931163 0.886
## ChemicalIDcedr.9.ene 0.125488 1.931163 0.065
## ChemicalIDcedrol 22.548238 1.931163 11.676
## ChemicalIDcis.thujopsene 17.277800 1.931163 8.947
## ChemicalIDcompound.1 1.726651 1.931163 0.894
## ChemicalIDcompound.2 0.115275 1.931163 0.060
## ChemicalIDcuparene 0.987034 1.931163 0.511
## ChemicalIDgamma.eudesmol 0.983322 1.931163 0.509
## ChemicalIDpara.cymene -0.330568 1.931163 -0.171
## ChemicalIDthujopsenal 1.616918 1.931163 0.837
## ChemicalIDwiddrol 5.815874 1.931163 3.012
## YearsSinceBurn:ChemicalIDalpha.cedrene 0.226317 0.141110 1.604
## YearsSinceBurn:ChemicalIDalpha.chamigrene 0.037633 0.141110 0.267
## YearsSinceBurn:ChemicalIDalpha.eudesmol 0.019210 0.141110 0.136
## YearsSinceBurn:ChemicalIDalpha.himachalene 0.025676 0.141110 0.182
## YearsSinceBurn:ChemicalIDalpha.pinene -0.002104 0.141110 -0.015
## YearsSinceBurn:ChemicalIDalpha.terpineol 0.041866 0.141110 0.297
## YearsSinceBurn:ChemicalIDbeta.acorenol -0.043200 0.141110 -0.306
## YearsSinceBurn:ChemicalIDbeta.cedrene 0.054302 0.141110 0.385
## YearsSinceBurn:ChemicalIDbeta.chamigrene 0.028045 0.141110 0.199
## YearsSinceBurn:ChemicalIDbeta.eudesmol 0.029696 0.141110 0.210
## YearsSinceBurn:ChemicalIDcedr.8.en.13.ol -0.170561 0.141110 -1.209
## YearsSinceBurn:ChemicalIDcedr.8.en.15.ol -0.021237 0.141110 -0.150
## YearsSinceBurn:ChemicalIDcedr.9.ene 0.026052 0.141110 0.185
## YearsSinceBurn:ChemicalIDcedrol -0.224855 0.141110 -1.593
## YearsSinceBurn:ChemicalIDcis.thujopsene 0.331832 0.141110 2.352
## YearsSinceBurn:ChemicalIDcompound.1 0.007509 0.141110 0.053
## YearsSinceBurn:ChemicalIDcompound.2 0.057963 0.141110 0.411
## YearsSinceBurn:ChemicalIDcuparene 0.077284 0.141110 0.548
## YearsSinceBurn:ChemicalIDgamma.eudesmol 0.023221 0.141110 0.165
## YearsSinceBurn:ChemicalIDpara.cymene 0.056406 0.141110 0.400
## YearsSinceBurn:ChemicalIDthujopsenal 0.014138 0.141110 0.100
## YearsSinceBurn:ChemicalIDwiddrol 0.026360 0.141110 0.187
## Pr(>|t|)
## (Intercept) 0.68886
## YearsSinceBurn 0.82304
## ChemicalIDalpha.cedrene 4.97e-05 ***
## ChemicalIDalpha.chamigrene 0.95987
## ChemicalIDalpha.eudesmol 0.85163
## ChemicalIDalpha.himachalene 0.90091
## ChemicalIDalpha.pinene 0.97975
## ChemicalIDalpha.terpineol 0.81757
## ChemicalIDbeta.acorenol 0.66771
## ChemicalIDbeta.cedrene 0.27301
## ChemicalIDbeta.chamigrene 0.84972
## ChemicalIDbeta.eudesmol 0.45974
## ChemicalIDcedr.8.en.13.ol 8.72e-05 ***
## ChemicalIDcedr.8.en.15.ol 0.37611
## ChemicalIDcedr.9.ene 0.94821
## ChemicalIDcedrol < 2e-16 ***
## ChemicalIDcis.thujopsene < 2e-16 ***
## ChemicalIDcompound.1 0.37156
## ChemicalIDcompound.2 0.95242
## ChemicalIDcuparene 0.60943
## ChemicalIDgamma.eudesmol 0.61077
## ChemicalIDpara.cymene 0.86413
## ChemicalIDthujopsenal 0.40271
## ChemicalIDwiddrol 0.00269 **
## YearsSinceBurn:ChemicalIDalpha.cedrene 0.10918
## YearsSinceBurn:ChemicalIDalpha.chamigrene 0.78978
## YearsSinceBurn:ChemicalIDalpha.eudesmol 0.89175
## YearsSinceBurn:ChemicalIDalpha.himachalene 0.85567
## YearsSinceBurn:ChemicalIDalpha.pinene 0.98811
## YearsSinceBurn:ChemicalIDalpha.terpineol 0.76678
## YearsSinceBurn:ChemicalIDbeta.acorenol 0.75958
## YearsSinceBurn:ChemicalIDbeta.cedrene 0.70048
## YearsSinceBurn:ChemicalIDbeta.chamigrene 0.84252
## YearsSinceBurn:ChemicalIDbeta.eudesmol 0.83338
## YearsSinceBurn:ChemicalIDcedr.8.en.13.ol 0.22716
## YearsSinceBurn:ChemicalIDcedr.8.en.15.ol 0.88041
## YearsSinceBurn:ChemicalIDcedr.9.ene 0.85358
## YearsSinceBurn:ChemicalIDcedrol 0.11148
## YearsSinceBurn:ChemicalIDcis.thujopsene 0.01896 *
## YearsSinceBurn:ChemicalIDcompound.1 0.95757
## YearsSinceBurn:ChemicalIDcompound.2 0.68137
## YearsSinceBurn:ChemicalIDcuparene 0.58407
## YearsSinceBurn:ChemicalIDgamma.eudesmol 0.86934
## YearsSinceBurn:ChemicalIDpara.cymene 0.68947
## YearsSinceBurn:ChemicalIDthujopsenal 0.92022
## YearsSinceBurn:ChemicalIDwiddrol 0.85187
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 13.69473)
##
## Null deviance: 36652 on 781 degrees of freedom
## Residual deviance: 10079 on 736 degrees of freedom
## AIC: 4312.3
##
## Number of Fisher Scoring iterations: 2tidy(mod1) ## # A tibble: 46 x 5
## term estimate std.error statistic p.value
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 (Intercept) 0.547 1.37 0.401 0.689
## 2 YearsSinceBurn -0.0223 0.0998 -0.224 0.823
## 3 ChemicalIDalpha.cedrene 7.88 1.93 4.08 0.0000497
## 4 ChemicalIDalpha.chamigrene -0.0972 1.93 -0.0503 0.960
## 5 ChemicalIDalpha.eudesmol 0.361 1.93 0.187 0.852
## 6 ChemicalIDalpha.himachalene -0.241 1.93 -0.125 0.901
## 7 ChemicalIDalpha.pinene 0.0490 1.93 0.0254 0.980
## 8 ChemicalIDalpha.terpineol 0.446 1.93 0.231 0.818
## 9 ChemicalIDbeta.acorenol 0.829 1.93 0.429 0.668
## 10 ChemicalIDbeta.cedrene 2.12 1.93 1.10 0.273
## # ... with 36 more rowstidy(mod1) %>%
filter(p.value <= 0.05) %>%
mutate(term = term %>% str_remove_all("ChemicalID"))## # A tibble: 6 x 5
## term estimate std.error statistic p.value
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 alpha.cedrene 7.88 1.93 4.08 4.97e- 5
## 2 cedr.8.en.13.ol 7.62 1.93 3.95 8.72e- 5
## 3 cedrol 22.5 1.93 11.7 5.12e-29
## 4 cis.thujopsene 17.3 1.93 8.95 2.93e-18
## 5 widdrol 5.82 1.93 3.01 2.69e- 3
## 6 YearsSinceBurn:cis.thujopsene 0.332 0.141 2.35 1.90e- 2Terminal -> git add Exam 3
git commit -m “Exam 3”
git push
My folder for Exam 3 is not on GitHub.